Use Keras and a CNN from Keras Applications pretrained on ImageNet, to classify the images in the birds dataset. Construct a confusion matrix that relates the bird classes with the 10 most frequent classes from ImageNet predicted by the model.
Use the pre-trained CNN model as a feature extractor. Create a new model that replaces the top part of the pretrained CNN with two layers of 256 and 6 neurons respectively.
Train the model with the training images from the bird dataset.
Evaluate the performance over the test dataset reporting the results in a confusion matrix. Discuss the results.